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Cloud-based video surveillance system using EFD-GMM for object detection

  • China University of Mining & Technology, Beijing

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Nowadays, new generation of video surveillance systems integrates lots of heterogeneous cameras to collect, process, and analyze video for detecting the objects of potential security threats. The existing systems tend to reach the limit in terms of scalability, data access anywhere, video processing overhead, and massive storage requirements. A novel cloud computing can provide scalable and powerful techniques for large-scale storage, processing, and dissemination of video data. Furthermore, the integration of cloud computing and video processing technology offers more possibilities for efficient deployment of surveillance systems. This paper deploys the framework of a cloud-based video surveillance system and proposes an EFD-GMM approach for object detection in the overhead video processing. A prototype surveillance system is also designed to validate the proposed approach. It finally shows that the proposed approach is more efficient than GMM in video processing of cloud-based system.

源语言英语
主期刊名Cloud Computing and Security - 2nd International Conference, ICCCS 2016, Revised Selected Papers
编辑Xingming Sun, Alex Liu, Elisa Bertino, Han-Chieh Chao
出版商Springer Verlag
261-272
页数12
ISBN(印刷版)9783319486703
DOI
出版状态已出版 - 2016
活动2nd International Conference on Cloud Computing and Security, ICCCS 2016 - Nanjing, 中国
期限: 29 7月 201631 7月 2016

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
10039 LNCS
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议2nd International Conference on Cloud Computing and Security, ICCCS 2016
国家/地区中国
Nanjing
时期29/07/1631/07/16

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